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dc.contributor.authorSánchez Daniel, Ángel 
dc.contributor.authorGarrido Rubio, Jesús
dc.contributor.authorMolina Medina, Antonio Jesús
dc.contributor.authorGil García, Laura 
dc.contributor.authorSapino, Francesco
dc.contributor.authorGonzález-Piqueras, José
dc.contributor.authorPérez Blanco, Carlos Dionisio 
dc.date.accessioned2026-02-16T09:43:49Z
dc.date.available2026-02-16T09:43:49Z
dc.date.issued2024
dc.identifier.citationSánchez-Daniel, Á., Garrido-Rubio, J., Molina-Medina, A. J., Gil-García, L., Sapino, F., González-Piqueras, J., & Pérez-Blanco, C. D. (2024). Sensitivity of water reallocation performance assessments to water use data. Water Resources and Economics, 48. https://doi.org/10.1016/J.WRE.2024.100252es_ES
dc.identifier.issn2212-4284
dc.identifier.urihttp://hdl.handle.net/10366/169816
dc.description.abstract[EN] The lack of detailed and reliable data on the estimates of water use has been a key limitation in informing sustainable, equitable and efficient water reallocations in the agricultural sector. Conventional water use data have been commonly obtained from surveys or agronomic models, which have limitations on accurately reflecting the actual water use. This paper integrates cutting-edge satellite-based water use data with an ensemble of four Calibrated Mathematical Programming Models (CMPM) (one Positive Multi-Attribute Utility Programming model, one Weighted Goal Programming model, and two Positive Mathematical Programming models) to assess and compare the performance of water reallocations under satellite-based versus conventional water use estimates. We apply these methods to the water-stressed Mancha Oriental Aquifer (MOA) in central Spain, where we simulate the impacts of a hypothetical temporary water reacquisition policy in 2017, the last dry year in record. We find that water use estimates obtained with conventional approaches (which range between 4916 m3/ha and 4510m3/ha, on average) are 13–24 % lower than satellite-based estimates (5577 m3/ha on average) during the dry year. Moreover, the water reacquisition simulation using the CMPM ensemble shows that the reserve prices (25–66 % higher) and buyback costs (26–67 % higher) derived from conventional water use data approaches are consistently and significantly higher than those derived from satellite-based water use estimates for all the elements of the ensemble, suggesting that a policy informed with satellite-based data could significantly reduce the costs of the reallocation.es_ES
dc.description.sponsorshipThe research leading to these results has been developed with the support of the Ministry of Science and Innovation's IRENE Project (Integrated socioeconomic and environmental modelling using remote sensing data for the management of unauthorized water abstractions), the PRIMA Foundation's TALANOA-WATER Project (Talanoa Water Dialogue for Transformational Adaptation to Water Scarcity under Climate Change), the EU Horizon Europe's TRANSCEND Project (Transformational and Robust Adaptation to Water Scarcity and Climate Change under Deep Uncertainty) and the EU Horizon Europe's REXUS Project (Managing Resilient Nexus Systems Through Participatory Systems Dynamics Modelling).es_ES
dc.format.mimetypeapplication/pdf
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectRemote sensinges_ES
dc.subjectPositive mathematical programminges_ES
dc.subjectBuyback programes_ES
dc.subjectCrop water usees_ES
dc.subjectWater scarcityes_ES
dc.titleSensitivity of water reallocation performance assessments to water use dataes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publishversionhttps://www.sciencedirect.com/science/article/pii/S2212428424000161?via%3Dihubes_ES
dc.subject.unesco5308 Economía Generales_ES
dc.subject.unesco5401.01 Distribución de Recursos Naturaleses_ES
dc.identifier.doi10.1016/J.WRE.2024.100252
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.journal.titleWater Resources and Economicses_ES
dc.volume.number48es_ES
dc.page.initial100252es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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